Research Article
Security and Privacy in Fog/Cloud-based IoT Systems for AI and Robotics
@ARTICLE{10.4108/airo.3616, author={Prabh Deep Singh and Kiran Deep Singh}, title={Security and Privacy in Fog/Cloud-based IoT Systems for AI and Robotics}, journal={EAI Endorsed Transactions on AI and Robotics}, volume={2}, number={1}, publisher={EAI}, journal_a={AIRO}, year={2023}, month={8}, keywords={Security and privacy, Artificial Intelligence, Robotics, Internet of Things, Fog Computing, Cloud Computing}, doi={10.4108/airo.3616} }
- Prabh Deep Singh
Kiran Deep Singh
Year: 2023
Security and Privacy in Fog/Cloud-based IoT Systems for AI and Robotics
AIRO
EAI
DOI: 10.4108/airo.3616
Abstract
Integration of Internet of Things (IoT) systems based on the fog or the cloud with Artificial Intelligence (AI) and Robotics has prepared the way for breakthrough advancements in a variety of different fields of business. However, these cross-disciplinary technologies present significant difficulties in terms of maintaining confidentiality and safeguarding data. This article digs into the issues of establishing robust security and protecting user privacy in IoT systems that are based in the fog or the cloud and are utilized for AI and robotics applications. This study gives insights into the possible hazards encountered by such interconnected systems by conducting an in-depth review of existing security threats, vulnerabilities, and privacy concerns. In addition, the study investigates cutting-edge security mechanisms, encryption approaches, access control strategies, and privacy-preserving solutions that can be utilized to safeguard data, communications, and user identities. The results of this study highlight the demand for comprehensive security and privacy solutions to support the mainstream deployment of Fog/Cloud-based Internet of Things systems in the field of artificial intelligence and robotics.
Copyright © 2023 P. D. Singh et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.